An adaptive, interacting, cluster-based model for predicting the transmission dynamics of COVID-19.

Ravinder, R; Singh, Sourabh; Bishnoi, Suresh; Jan, Amreen; Sharma, Amit; Kodamana, Hariprasad; Krishnan, N M Anoop

Ravinder, R; Singh, Sourabh; Bishnoi, Suresh; Jan, Amreen; Sharma, Amit; Kodamana, Hariprasad; Krishnan, N M Anoop.

Afiliación

Ravinder R; Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Singh S; Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Bishnoi S; Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Jan A; Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Sharma A; Molecular Medicine Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Road, New Delhi, 110 067, India.
Kodamana H; Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.
Krishnan NMA; Department of Civil Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India.

Heliyon ; 6(12): e05722, 2020 Dec.

Article en En | MEDLINE | ID: mdl-33367130

Palabras clave

COVID-19; Computational mathematics; Effective reproduction number; Epidemiology; Infectious disease; Mathematical modeling; Microbiology; Public health; RT; Transmission dynamics

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2020 Tipo del documento: Article País de afiliación: India Pais de publicación: Reino Unido

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